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Agent skill

A2ui Add Eval Datapoint

by a2ui-project in a2ui-project/a2ui

Step-by-step workflow for adding and verifying new evaluation data points in the A2UI evaluation suite.

Apache-2.0Auto-check passedDevelopment

Install A2ui Add Eval Datapoint

skills CLI
$ npx skills add a2ui-project/a2ui --skill a2ui-add-eval-datapoint -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install a2ui-project/a2ui a2ui-add-eval-datapoint --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/a2ui-project/a2ui.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/a2ui-add-eval-datapoint .claude/skills/a2ui-add-eval-datapoint && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
a2ui-add-eval-datapoint
GitHub stars
17k
Token cost
~811 tokens
SKILL.md length
301 words
Files
1
Skills in repo
20
Repo updated
First seen
Licence
Apache-2.0

At a glance

Step-by-step workflow for adding and verifying new evaluation data points in the A2UI evaluation suite.

  • Works in 5 steps: Unlock Transcrypt → Author the data point → Validate schema compliance → …
  • Development work in your project
  • SKILL.md covers References and Step-by-step workflow
  • Calls uv and git

What it does

A2ui Add Eval Datapoint is an agent skill from a2ui-project/a2ui. Step-by-step workflow for adding and verifying new evaluation data points in the A2UI evaluation suite.

Its SKILL.md is about 810 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. The licence is Apache-2.0.

When your agent uses it

  • Development work in your project

Example prompts

  • “/a2ui-add-eval-datapoint”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Unlock Transcrypt
  2. Author the data point
  3. Validate schema compliance
  4. Run an evaluation on the new data point
  5. Verify encryption and commit

What it can do on your machine

Read from SKILL.md and the folder at commit db43065. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • uv
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv and git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

A2ui Add Eval Datapoint loads about 811 tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 301 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~811

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from a2ui-project/a2ui at commit db43065, republished under its Apache-2.0 licence (© a2ui-project). 301 words, ~811 tokens.

Download SKILL.mdSave it as .claude/skills/a2ui-add-eval-datapoint/SKILL.md (or your agent's skills folder).
name
a2ui-add-eval-datapoint
description
Step-by-step workflow for adding and verifying new evaluation data points in the A2UI evaluation suite.

Adding and verifying A2UI evaluation data points

Use this skill when adding new data points or datasets to the A2UI evaluation framework in eval/.

References

For full architecture and setup details, consult:

  • eval/CONTRIBUTING_USE_CASES.md: The authoritative contributor guide for evaluation use cases, containing field definitions, context rules, and unencrypted multi-turn examples.
  • eval/README.md: Evaluation quickstart, Transcrypt setup, and CLI flags.
  • eval/DESIGN.md: Architecture, multi-stage scorers, and encryption-at-rest design.
  • eval/datasets/dataset_schema.json: Formal JSON Schema defining required fields and structural rules for evaluation data points.

Step-by-step workflow

1. Unlock Transcrypt

Datasets in eval/datasets/ are encrypted at rest. Unlock Transcrypt locally before authoring (ask an A2UI team member for the password):

bash
cd eval
bin/transcrypt -y -c aes-256-cbc -p <PASSWORD>
2. Author the data point

Create or update a dataset file in eval/datasets/<dataset_name>.yaml (e.g. eval/datasets/my_dataset.yaml).

Every data point must conform to the JSON Schema in eval/datasets/dataset_schema.json and follow the authoring guidelines in eval/CONTRIBUTING_USE_CASES.md.

For a complete unencrypted reference example of a multi-turn conversation with system instructions, tool calls (including unrelated background tool calls), tool responses, and a judging target rubric, inspect eval/examples/example_eval_case.json.

Key authoring requirements from eval/CONTRIBUTING_USE_CASES.md:

  • Include the full multi-turn conversation history (messages), including assistant function calls (tool_calls) and tool responses (role: tool). Do not use single-turn prompts.
  • Write the target as a qualitative judging rubric for the LLM-as-a-judge (what UI components must appear, data binding rules, and what errors to penalize). Do not include a hardcoded JSON string, as that ties the evaluation to a particular inference format.
3. Validate schema compliance

Verify that all data points satisfy eval/datasets/dataset_schema.json:

bash
cd eval
uv run python -m pytest tests/test_dataset.py
4. Run an evaluation on the new data point

Always execute an evaluation run on the newly added dataset to verify model inference and scoring:

bash
cd eval
# Quick validation on gemini-3.1-flash-lite
uv run main.py --dataset my_dataset --sanity

# Full evaluation check
uv run main.py --dataset my_dataset

View the interactive traces and judging rationales:

bash
uv run inspect view start
5. Verify encryption and commit

When staging changes, Git applies the Transcrypt clean filter. Confirm that the staged file is encrypted ciphertext before committing:

bash
# Stage the new dataset file
git add eval/datasets/my_dataset.yaml

# Verify staged content is encrypted ciphertext (not plaintext)
git diff --cached eval/datasets/my_dataset.yaml

# Commit the encrypted data point
git commit -m "feat(eval): add my_dataset evaluation data points"

© a2ui-project, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/a2ui-add-eval-datapoint of a2ui-project/a2ui.

Open the folder on GitHubat commit db43065

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Categories

Questions about A2ui Add Eval Datapoint

What does A2ui Add Eval Datapoint do?

Step-by-step workflow for adding and verifying new evaluation data points in the A2UI evaluation suite. A2ui Add Eval Datapoint is an agent skill from a2ui-project/a2ui. Step-by-step workflow for adding and verifying new evaluation data points in the A2UI evaluation suite.

When should I use A2ui Add Eval Datapoint?

A2ui Add Eval Datapoint fits situations like: development work in your project.

How do I install A2ui Add Eval Datapoint in Claude Code?

Run `npx skills add a2ui-project/a2ui --skill a2ui-add-eval-datapoint -a claude-code`. Or copy the skill folder (.agents/skills/a2ui-add-eval-datapoint in a2ui-project/a2ui) into .claude/skills/a2ui-add-eval-datapoint in your project. Claude Code loads it when a task matches its description.

How do I install A2ui Add Eval Datapoint in Codex?

Run `npx skills add a2ui-project/a2ui --skill a2ui-add-eval-datapoint -a codex`. Or copy the skill folder (.agents/skills/a2ui-add-eval-datapoint in a2ui-project/a2ui) into .agents/skills/a2ui-add-eval-datapoint in your project. Codex loads it when a task matches its description.

Can I use A2ui Add Eval Datapoint in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add a2ui-project/a2ui --skill a2ui-add-eval-datapoint -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/a2ui-add-eval-datapoint, .gemini/skills/a2ui-add-eval-datapoint, .github/skills/a2ui-add-eval-datapoint and .opencode/skills/a2ui-add-eval-datapoint in your project.

What does A2ui Add Eval Datapoint need to run?

Going by SKILL.md and its folder, A2ui Add Eval Datapoint needs the command-line tools its instructions call (uv and git). Our summary lists: Python 3.

Does A2ui Add Eval Datapoint access the network?

SKILL.md contains no URLs. Its commands use uv and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is A2ui Add Eval Datapoint safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does A2ui Add Eval Datapoint use?

A2ui Add Eval Datapoint is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does A2ui Add Eval Datapoint use?

About 811 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to A2ui Add Eval Datapoint?

Skills that share tags, products or a category with A2ui Add Eval Datapoint: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains A2ui Add Eval Datapoint?

a2ui-project (a GitHub organization) maintains it in a2ui-project/a2ui, which has 16,617 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 8, 2026.

Source: a2ui-project/a2ui on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.